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Laboratory experiments next to a variety of observations, especially in subduction zones, have explored the existence of a premonitory stable slow slip growth phase preceding large earthquakes. These phenomena play an important role in the earthquake cycle and thus precise imaging and monitoring of these events are of great significance. In the literature, ENIF (extended network inversion filter) has been proposed as a rigorous algorithm capable of isolating signal from different types of noise and thereby provides us with deep insight into spatio-temporal evolution of slow slip events. Despite its considerable advantages, ENIF still suffers from some limitations. ENIF applies Tikhonov method of regularization with a quadratic form of cost function. While anomalous slip regions have clear contrast with the background slip in reality, Tikhonov regularization tends to over smooth (globally smooth) the slipping portion on the estimated images. In order to avoid over smoothing phenomenon, we have incorporated into ENIF an image segmentation step which tries to preserve edges of slow-slip event. As a second limitation, due to the nonlinearity imposed by such constraint as non-negativity of slip rate, uncertainty propagation through model is not simple. As the core of ENIF, EKF (extended Kalman filter), performs uncertainty propagation by linearization of nonlinear model using Jacobian and Hessian matrices. As an alternative for EKF, we have also investigated the application of UKF (unscented Kalman filter) which uses UT (unscented transform) for uncertainty propagation. Finally, we tested our proposed algorithm using a low signal to noise ratio synthetic data set. The results show a significant improvement in the performance of ENIF when the segmentation step is incorporated into the algorithm.

This study introduce a new frequency parameter called $$\tau_{\text{fcwt}}$$ τfcwt , which can be used to estimate earthquake magnitude on the basis of the first few seconds of P-waves, using the waveforms of earthquakes occurring in Japan. This new parameter is introduced using continuous wavelet transform as a tool for extracting the frequency contents carried by the first few seconds of P-wave. The empirical relationship between the logarithm of $$\tau_{\text{fcwt}}$$ τfcwt within the initial 4 s of a waveform and magnitude was obtained. To evaluate the precision of $$\tau_{\text{fcwt}}$$ τfcwt , we also calculated parameters $$\tau_{\text{p}}^{ \hbox{max} }$$ τpmax and $$\tau_{\text{c}}$$ τc . The average absolute values of observed and estimated magnitude differences ($$|M_{\text{est}} - M_{\text{obs}} |$$ |Mest-Mobs| ) were 0.43, 0.49, and 0.66 units of magnitude, as determined using $$\tau_{\text{p}}^{ \hbox{max} }$$ τpmax , $$\tau_{\text{c}}$$ τc , and $$\tau_{\text{fcwt}}$$ τfcwt , respectively. For earthquakes with magnitudes greater than 6, these values were 0.34, 0.56, and 0.44 units of magnitude, as derived using $$\tau_{\text{p}}^{ \hbox{max} }$$ τpmax , $$\tau_{\text{c}}$$ τc , and $$\tau_{\text{fcwt}}$$ τfcwt , respectively. The $$\tau_{\text{fcwt}}$$ τfcwt parameter exhibited more precision in determining the magnitude of moderate- and small-scale earthquakes than did the $$\tau_{\text{c}}$$ τc -based approach. For a general range of magnitudes, however, the $$\tau_{\text{p}}^{ \hbox{max} }$$ τpmax -based method showed more acceptable precision than did the other two parameters.

By analyzing the seismic catalogue of Iran, the probability distributions of interoccurrence times of earthquakes were investigated for different seismotectonic settings. Several probability distributions were applied to data from major seismotectonic provinces in different cut-off magnitudes and the distribution parameters were determined through the method of maximum likelihood. With the help of goodness-of-fit tests (AIC and BIC criteria based on information theory, Kolmogorov–Smirnov test) and the coefficient of determination, we have found that the gamma statistics and generalized normal statistics coexist in interoccurrence time statistics. Our results imply that a transition from a generalized normal regime to a gamma regime occurs if the threshold magnitude in certain seismotectonic regions (Alborz–Azarbayejan, Zagros, and Central-East Iran) is changed.

Seismic hazard assessment and zoning of the Kermanshah-Sanandaj region in western Iran is conducted using probabilistic approach. Two maps have been prepared to indicate the earthquake hazard of the region in the form of iso-acceleration contour lines. They display a probabilistic estimate of peak ground acceleration (PGA) over bedrock for the return periods of 475 and 50 years. A uniform catalog of earthquakes containing historical and instrumental events covering the period from the eleventh century A.D. to 2003 is used. Twelve potential seismic sources are modeled as area sources in the region. Seismicity parameters are evaluated using the method in which magnitude uncertainty and incompleteness of earthquake data are considered. Seismic hazard assessment is carried out for a grid of 357 points with 0.1° intervals using the SEISRISKIII computer program for the study area encompassed by the 46–48°Elongitudes and 34–36°Nlatitudes. This region includes the most active segments of the Zagros Main Recent Fault; among them, the Sahneh and Nahavand faults have a well-known history of intense seismic activity. PGA values for this region are estimated to be 0.35 gand 0.20 gfor 475- and 50-years return periods, respectively.

A total of 235 potential seismic sources in Iran and neighboring regions are delineated based on available geological, geophysical, tectonic and earthquake data for seismic hazard assessment of the country. In practice, two key assumptions are considered; first, the assumption of earthquake repeatedness, implying that major earthquakes occur preferentially near the sites of previous earthquakes; second, the assumption of tectonic analogy, which implies that structures of analogous tectonic setting are capable of generating same size earthquakes. A two-step procedure is applied for delineation of seismic sources: first, demarcation of seismotectonic provinces; second, determination of potential seismic sources. Preferentially, potential seismic sources are modeled as area sources, in which the configuration of each source zone is controlled, mainly, by the extent of active faults, the mechanism of earthquake faultings and the seismogenic part of the crust.